Journal of Theoretical & Computational Science
Open Access
ISSN: 2376-130X
+44 1223 790975
ISSN: 2376-130X
+44 1223 790975
Romana Ishrat
Centre for Interdisciplinary Research in Basic Sciences,
Jamia Millia Islamia, New Delhi
India
Research Article
In Silico Based Analysis of CKD Expressions Data in Correlation with Diabetes Mellitus Unveils Biomarker Gene
Author(s): Mohammed Murshad Ahmed, Safia Tazyeen, Aftab Alam, Anam Farooqui, Shahnawaz Ali, Zubbair Malik and Romana IshratMohammed Murshad Ahmed, Safia Tazyeen, Aftab Alam, Anam Farooqui, Shahnawaz Ali, Zubbair Malik and Romana Ishrat
Chronic kidney disease (CKD) is becoming an extensive public health problem worldwide. The current anxiety of disease might be due to the change of the underlying pathogenicity. The aim of our study was to provide a detailed analysis of microarray gene expression data of CKD in correlation with diabetes and identification of biomarker genes. Here, Affymetrix expression arrays were used to identify differentially expressed genes in 22 and 69 samples of CKD and diabetes respectively. It further outlines few of the principal biological alterations observed in the CKD state and depicts specific procedures for conducting quality assessment of Affymetrix Gene chip using GEO datasets (GSE70528, GSE11045) and also illustrates quality control packages to remark the visualization for detailed analysis. We identified 912 differentially expressed genes in CKD and 629 in diabetes. From extensive c.. View More»
DOI:
10.4172/2376-130X.1000156